CN114384934A - Method for acquiring air collision probability of unmanned aerial vehicle - Google Patents
Method for acquiring air collision probability of unmanned aerial vehicle Download PDFInfo
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Abstract
The invention discloses a method for acquiring the air collision probability of an unmanned aerial vehicle, which comprises the following steps: acquiring information of a target unmanned aerial vehicle, inputting the information into a preset flight collision model, acquiring the target length, the target width and the target height of the target unmanned aerial vehicle, acquiring the key length, the key width and the key height corresponding to the target unmanned aerial vehicle, and constructing a near layer corresponding to the inner side collision template; the method comprises the steps of obtaining a first target probability value, a second target probability value and a third target probability value corresponding to a target unmanned aerial vehicle, obtaining a first relative speed, a second relative speed and a third relative speed of the unmanned aerial vehicle, and further calculating and obtaining the collision probability of the target unmanned aerial vehicle and a preset adjacent unmanned aerial vehicle.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle collision probability, in particular to a method for acquiring unmanned aerial vehicle air collision probability.
Background
The low-altitude airspace is an important natural resource, which contains huge economic value, and the reasonable development, utilization and management of the low-altitude airspace is an important way for the world countries to enter the aeronautical strong countries. In recent years, with the gradual opening of low-altitude airspace and the development of technologies, the application of unmanned aerial vehicles is more and more extensive, and a plurality of fields such as personal entertainment, pipeline inspection, traffic monitoring, search and rescue, agricultural plant protection, public security fire control, freight transportation and the like are covered at present. However, as the flight volume of various unmanned aerial vehicles is rapidly increased, the flight density of the unmanned aerial vehicles in the airspace is gradually increased, so that the flight safety of the unmanned aerial vehicles in the air operation is ensured, the unmanned aerial vehicles are prevented from colliding in the air, and the method is an important premise for fully utilizing the low-altitude airspace resources in the future.
In order to prevent the unmanned aerial vehicles from colliding in the air, a safe operation interval between the unmanned aerial vehicles needs to be established through research, and the establishment of the real-time air collision probability of the unmanned aerial vehicles is the basis for establishing the safe interval.
Disclosure of Invention
In order to solve at least one of the problems in the prior art, the technical scheme adopted by the application comprises the following steps:
s100, acquiring original data corresponding to the target unmanned aerial vehicle, inputting the original data corresponding to the target unmanned aerial vehicle into a preset flight collision model, and acquiring the target length delta of the target unmanned aerial vehiclexTarget width deltayAnd a target height δz；
S200, based on deltax、δyAnd deltazAnd obtaining the key length S corresponding to the target unmanned aerial vehiclexCritical width SyAnd critical height SzConstructing a near layer corresponding to the inner side collision template on the basis of the inner side collision template in the flight collision template;
s300, based on deltax、δy、δz、Sx、SyAnd SzAcquiring a first corresponding to the target unmanned aerial vehicleTarget probability value PxSecond target probability value PyAnd a third target probability value Pz；
S400, acquiring a first relative speed u, a second relative speed v and a third relative speed w of the unmanned aerial vehicle according to u, v, w and Px、PyAnd PzAnd acquiring the collision probability Q of the target unmanned aerial vehicle.
The application has at least the following technical effects: in the preset flight collision model of the information input value of the target unmanned aerial vehicle, the corresponding key length, key width and key height are obtained according to the length, width and height of the target unmanned aerial vehicle, so that the first target probability value, the second target probability value and the third target probability value of the target unmanned aerial vehicle are obtained, the collision probability of the target unmanned aerial vehicle is obtained according to the first relative speed, the second relative speed and the third relative speed, and the accuracy of determining the real-time air collision probability of the target unmanned aerial vehicle is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without inventive efforts.
Fig. 1 is a schematic flow chart of a method for acquiring an aerial collision probability of an unmanned aerial vehicle according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. A process may be terminated when its operations are completed, but may have additional steps not included in the figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.
The embodiment provides a method for acquiring an air collision probability of an unmanned aerial vehicle, as shown in fig. 1, the method includes the following steps:
s100, acquiring original data corresponding to the target unmanned aerial vehicle, inputting the original data corresponding to the target unmanned aerial vehicle into a preset flight collision model, and acquiring the target length delta of the target unmanned aerial vehiclexTarget width deltayAnd a target height δz。
In particular, the raw data comprises a length λ of the target dronexWidth lambda of target droneyAnd height λ of target dronezIt can be understood that: when the target drone is deployed, λxFuselage length, λ, of the target droneyIs the length between two wings of the target unmanned aerial vehicle, lambdazIs the fuselage height of the target drone.
Further, δx＝2λx，δy＝2λy，δz＝2λzIt can be understood that: the primary data that target unmanned aerial vehicle corresponds is in handle in the flight collision model, wherein, flight collision model includes inboard collision template, inboard collision template is the cuboid, the flight collision model is in the flight collision model, the flight collision model is in the form of a solid, the primary data that the target unmanned aerial vehicle corresponds is in the flight collision model is handled, wherein, flight collision model includes inboard collision template, inboard collision template is the cuboid, the flight collision model is in the form of a solid, the primary data that the target unmanned aerial vehicle corresponds is in the flight collision modelThe length of inboard collision template is as target unmanned aerial vehicle's target length, the width of inboard collision template is as target unmanned aerial vehicle's target width, the height of inboard collision template is as target unmanned aerial vehicle's target height, can change the collision template of cuboid into with this kind of anomalous object of unmanned aerial vehicle and only need handle to the data that the collision template corresponds, is favorable to obtaining the collision probability in the equidirectional not of taking out.
S200, based on deltax、δyAnd deltazAnd obtaining the key length S corresponding to the target unmanned aerial vehiclexCritical width SyAnd critical height Sz。
Specifically, in step S200, based on the inner side collision template, a neighboring layer corresponding to the inner side collision template is built in the flight collision model, where the neighboring layer is a cylinder, and a person skilled in the art can know a method for building the neighboring layer in the flight collision model, which is not described herein again.
Further, the diameter of the adjacent layer is taken as Sx，SxFor characterizing a minimum safety separation and S of a target drone in a first directiony＝Sx，SyThe minimum safety distance of the marked unmanned aerial vehicle in the second direction is represented, and the height of the adjacent layer is taken as Sz，SzThe unmanned aerial vehicle is used for representing the minimum safe distance of a target unmanned aerial vehicle in a third direction, wherein the target unmanned aerial vehicle is another unmanned aerial vehicle except the target unmanned aerial vehicle; can be approximate to the cylinder with the layer that closes on that unmanned aerial vehicle corresponds, guaranteed the scope that unmanned aerial vehicle does not collide, improved the accuracy of confirming the real-time aerial collision probability of unmanned aerial vehicle.
S300, based on deltax、δy、δz、Sx、SyAnd SzAcquiring a first target probability value P corresponding to the target unmanned aerial vehiclexSecond target probability value PyAnd a third target probability value PzWherein, in the step (A),
Pxthe following conditions are met:
Pythe following conditions are met:
Pzthe following conditions are met:
Specifically, in step S300, the method further includes the following steps:
s301, establishing a three-dimensional model corresponding to the target unmanned aerial vehicle, wherein the x-axis direction of the three-dimensional model is a first direction, the y-axis direction of the three-dimensional model is a second direction, and the z-axis direction of the three-dimensional model is a third direction;
s303, obtaining a first course angle and a second course angle of the target unmanned aerial vehicle, and obtaining a first course value and a second course value according to the first course angle, the second course angle and the three-dimensional model.
Specifically, in step S301, the first direction refers to a horizontal direction in which the target drone is located, and may be understood as: taking the length direction of the body of the target unmanned aerial vehicle as the horizontal direction; the second direction refers to the vertical direction that target unmanned aerial vehicle is in, can understand as: taking the length direction of the wings of the target unmanned aerial vehicle as the vertical direction; the third direction is the vertical direction that target unmanned aerial vehicle is in, can understand as: the direction of the height of the body of the target unmanned aerial vehicle is taken as the vertical direction.
Specifically, the first heading value is a difference value of a first heading angle between the target unmanned aerial vehicle and the designated unmanned aerial vehicle in the first direction, wherein the first heading angle is an included angle between a longitudinal axis of the target unmanned aerial vehicle and a preset key mark position, and a middle axis corresponding to a fuselage of the target unmanned aerial vehicle is used as the longitudinal axis of the target unmanned aerial vehicle.
Specifically, the second heading value is a difference value of a second heading angle between the target unmanned aerial vehicle and the designated unmanned aerial vehicle in the third direction, wherein the second heading angle is an included angle between a transverse axis of the unmanned aerial vehicle and a north pole of the earth, a middle axis corresponding to a wing direction and a half of a fuselage length of the target unmanned aerial vehicle is taken as the transverse axis of the target unmanned aerial vehicle, and the transverse axis is perpendicular to the longitudinal axis.
(y) satisfies the following condition:
Preferably, the first and second electrodes are formed of a metal,
the determination may be made with reference to the satisfaction of f (y), wherein,
the following conditions are met:
further, the first mean value is a standard deviation corresponding to a position error of the target unmanned aerial vehicle in the second direction, and can be set by a person skilled in the art according to actual needs, which is not described herein again.
Further, the first root variance value is a root variance value and σ corresponding to the position error of the target unmanned aerial vehicle in the second direction1(t) satisfies the following condition:
Preferably, the first and second electrodes are formed of a metal,
the determination may be made with reference to the coincidence condition of f' (z), wherein,
the following conditions are met:
further, the second average value is a standard deviation corresponding to the position error in the third direction, and may be set by a person skilled in the art according to actual requirements, which is not described herein again.
Further, the second root variance value is a root variance value corresponding to the position error in the third direction, and σ2(t) satisfies the following condition:
Preferably, the first and second electrodes are formed of a metal,
and is
Preferably, t is0＝1s。
S400, acquiring a first relative speed u, a second relative speed v and a third relative speed w of the unmanned aerial vehicle according to u, v, w and Px、PyAnd PzAnd acquiring the collision probability Q of the target unmanned aerial vehicle, wherein Q meets the following conditions:
specifically, u refers to a relative speed between the target drone and the designated drone in the first direction, v refers to a relative speed between the target drone and the designated drone in the second direction, and w refers to a relative speed between the target drone and the designated drone in the second direction. Through the combination of collision probabilities in three directions and the calculation of adding the speeds of the unmanned aerial vehicle in the three directions into the collision probabilities, the accuracy of determining the collision probabilities of the unmanned aerial vehicle in all directions is improved.
Specifically, the raw data corresponding to the target unmanned aerial vehicle includes the relative speed of the target unmanned aerial vehicle, which is not described herein again.
Firstly, obtaining the target length, the target width and the target height of a target unmanned aerial vehicle; acquiring a key length, a key width and a key height corresponding to the target unmanned aerial vehicle based on the target length, the target width and the target height, and constructing a near layer corresponding to an inner side collision template in a flight collision template based on the inner side collision template; based on target length, target width, target height, critical length, critical width, and critical heightzAcquiring a first target probability value, a second target probability value and a third target probability value corresponding to the target unmanned aerial vehicle; acquiring a first relative speed, a second relative speed and a second relative speed of a target unmanned aerial vehicleAcquiring collision probability of the target unmanned aerial vehicle according to the three relative speeds and the first target probability value, the second target probability value, the third target probability value, the first relative speed, the second relative speed and the third relative speed; can be effective and accurate confirm unmanned aerial vehicle's collision probability, avoid unmanned aerial vehicle collision in the air, lead to unmanned aerial vehicle to damage.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (7)
1. A method for acquiring the air collision probability of an unmanned aerial vehicle is characterized by comprising the following steps:
s100, acquiring original data corresponding to the target unmanned aerial vehicle, inputting the original data corresponding to the target unmanned aerial vehicle into a preset flight collision model, and acquiring the target length delta of the target unmanned aerial vehiclexTarget width deltayAnd a target height δz；
S200, based on deltax、δyAnd deltazAnd obtaining the key length S corresponding to the target unmanned aerial vehiclexCritical width SyAnd critical height SzConstructing a near layer corresponding to the inner side collision template on the basis of the inner side collision template in the flight collision template;
s300, based on deltax、δy、δz、Sx、SyAnd SzAcquiring a first target probability value P corresponding to the target unmanned aerial vehiclexSecond target probability value PyAnd a third target probability value Pz；
S400, acquiring a first relative speed u, a second relative speed v and a third relative speed w of the target unmanned aerial vehicle according to u, v, w and Px、PyAnd PzAnd acquiring the collision probability Q of the target unmanned aerial vehicle.
2. The method for acquiring the air collision probability of the unmanned aerial vehicle as claimed in claim 1, wherein in step S200, the adjacent layer is cylindrical.
3. The method for acquiring the air collision probability of unmanned aerial vehicle according to claim 1, wherein in step S300, P isxThe following conditions are met:
4. The method for acquiring the air collision probability of unmanned aerial vehicle according to claim 1, wherein in step S300, P isyThe following conditions are met:
5. The method for acquiring the air collision probability of unmanned aerial vehicle according to claim 1, wherein in step S300, P iszThe following conditions are met:
6. The method for acquiring the air collision probability of the unmanned aerial vehicle according to claim 1, wherein in step S300, the method further comprises the following steps:
s301, establishing a three-dimensional model corresponding to the target unmanned aerial vehicle, wherein the x-axis direction of the three-dimensional model is a first direction, the y-axis direction of the three-dimensional model is a second direction, and the z-axis direction of the three-dimensional model is a third direction;
s303, obtaining a first course angle and a second course angle of the target unmanned aerial vehicle, and obtaining a first course value and a second course value according to the first course angle, the second course angle and the three-dimensional model.
7. The method for acquiring the air collision probability of the unmanned aerial vehicle according to claim 1, wherein in step S400, Q satisfies the following condition:
wherein, u indicates in the first direction, relative velocity between target unmanned aerial vehicle and the adjacent unmanned aerial vehicle of predetermineeing, and v indicates in the second direction, relative velocity between target unmanned aerial vehicle and the adjacent unmanned aerial vehicle of predetermineeing, and w indicates in the second direction, relative velocity between target unmanned aerial vehicle and the adjacent unmanned aerial vehicle of predetermineeing.
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